Agent-Based Model for Phenotypic Prediction Using Genomic and Environmental Data

Abstract

One of the means to increase in-éeld crop yields is the use of software tools to predict future yield values using past in-éeld trials and plant genetics. The traditional, statistics-based approaches lack environmental data integration and are very sensitive to missing and/or noisy data. In this paper, we show how using a cooperative, adaptive Multi-Agent System can overcome the drawbacks of such algorithms. The system resolves the problem in an iterative way by a cooperation between the constraints, modelled as agents. Results show a good convergence of the algorithm. Complete tests to validate the provided solution quality are still in progress.